The advantages & dangers of using AI to analyze data — George Davis // Frame AI
- Part 1Understanding unstructured customer interaction data — George Davis // Frame AI
- Part 2 The advantages & dangers of using AI to analyze data — George Davis // Frame AI
Show Notes
-
02:04The main ways AI driven data analysis can go astrayExcitement about AI's potential to uncover new insights can lead to aimless exploration without clear business objectives. Additionally, neglecting to consider the imperfections in data models can result in inaccurate and unreliable outcomes.
-
03:34Maximizing value and avoiding pitfalls in data projectsSuccessful projects involve iterative planning, and it's crucial to avoid treating data initiatives as one-time efforts to prevent projects from becoming obsolete. Furthermore, efforts should be made to measure and enhance the inclusivity of AI-generated value for all customers.
-
06:59How to overcome the limitation of LLMs for multilingual customer interactionWhile these models are often biased towards English due to training data availability, businesses should consider economic rewards and allocate resources to address the limitations. Inclusivity requires investment and proactive planning from the outset of a project.
-
10:32Enhancing commercial interactions across languages with AINowadays, the latest large language models incorporate substantial multi-language datasets. While accuracy varies, for the top 16 most spoken languages globally, AI can enhance commercial interactions and bring value.
-
11:48Privacy and data governance considerations when adopting AI solutionsBusinesses often face trade-offs between sharing data with external platforms for convenience and maintaining control over personal information. In response, businesses must prioritize solutions that enable privacy and data governance when adopting AI solutions.
-
14:05The importance of guiding AI Interactions with human supervisionUsing AI to automate customer interactions requires careful supervision. While AI can surface useful patterns and insights, interactions with customers should involve human oversight to avoid distressing or harmful outcomes as AI alignment is not a problem we've yet solved.
-
19:05Balancing the potential and risks of AI automation in customer interactionsMany businesses are rushing into automation, leading to unintended consequences for customers and their workforce. Instead, businesses should consider how AI can help humans do their jobs better and help team collaboration by moving data from one team to another.
Quotes
-
"Data projects can fail from a business perspective if you don't plan for iteration or lack a business objective at the beginning." - George Davis
-
"No data model is perfect, and you need to think hard about what types of errors you can tolerate." - George Davis
-
"Every large language model requires some amount of domain adaptation to do a good job in analyzing data." - George Davis
-
"For the 16 most spoken languages around the world, AI can definitely add value to commercial interactions in all 16 of those languages at this point." - George Davis
-
"When rapidly adopting AI solutions, its easy to skip the steps of being careful about where your data is coming from and where it's going. But there are solutions to exercise good governance over your customer's data." - George Davis
-
"There's a joke that there can be unsupervised machine learning, but there should never be unsupervised machine learning applications." - George Davis
-
"When you're using AI to do automated things, think very hard about the limitations of that interaction and how well that AI can understand what's going to be upsetting to a customer or not." - George Davis
-
"Many businesses over the next 10 years will move too fast on automation use cases" - George Davis
- Part 1Understanding unstructured customer interaction data — George Davis // Frame AI
- Part 2 The advantages & dangers of using AI to analyze data — George Davis // Frame AI
Up Next:
-
Part 1Understanding unstructured customer interaction data — George Davis // Frame AI
George Davis, Founder and CEO of Frame AI, explores how to use AI for analyzing unstructured customer interaction data. Smartphones boosted customer interaction data collection for companies, but analyzing this data was costly and challenging. However, companies like Frame AI seized the opportunity to use advanced natural language understanding for insights and to solve problems with that customer interaction data. Today, George discusses understanding unstructured customer interaction data.
Play Podcast -
Part 2The advantages & dangers of using AI to analyze data — George Davis // Frame AI
George Davis, Founder and CEO of Frame AI, explores how to use AI for analyzing unstructured customer interaction data. Numerous businesses are hastily embracing AI for automating customer interactions and data analysis. Despite the initial high ROI offered by AI, failing to adopt a strategic approach can lead to long-term consequences. Today, George discusses the advantages and dangers of using AI to analyze data.
